Concept
Convergence of random variables
Related publications (272)
Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas
Anthony Christopher Davison, Igor Rodionov
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...
Oxford2024Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning
Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...
EPFL2024Stochastic pairwise preference convergence in Bayesian agents
Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...
2024Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields
Marcos Rubinstein, Farhad Rachidi-Haeri, Hamidreza Karami, Elias Per Joachim Le Boudec, Nicolas Mora Parra
Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...
2024Full-F turbulent simulation in a linear plasma device using a gyro-moment approach
Paolo Ricci, Baptiste Jimmy Frei
Simulations of plasma turbulence in a linear plasma device configuration are presented. These simulations are based on a simplified version of the gyrokinetic (GK) model proposed by Frei et al. [J. Plasma Phys. 86, 905860205 (2020)], where the full-F distr ...
Melville2024Residual-based attention in physics-informed neural networks
Nikolaos Stergiopoulos, Sokratis Anagnostopoulos
Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...
Lausanne2024Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations
Given two jointly distributed random variables (X,Y), a functional representation of X is a random variable Z independent of Y, and a deterministic function g(⋅,⋅) such that X=g(Y,Z). The problem of finding a minimum entropy functional representation is kn ...
2023A NEW PROOF OF THE ERDOS-KAC CENTRAL LIMIT THEOREM
Thomas Mountford, Michael Cranston
In this paper we use the Riemann zeta distribution to give a new proof of the Erdos-Kac Central Limit Theorem. That is, if zeta(s) = Sigma(n >= 1) (1)(s)(n) , s > 1, then we consider the random variable X-s with P(X-s = n) = (1) (zeta) ( ...
Providence2023Sensitivity to user mischaracterizations in electric vehicle charging
In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...
ELSEVIER2023Robust optimization of control parameters for WEC arrays using stochastic methods
This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...
MOX Modeling and Scientific Computing2023